张智, 陈艳波, 刘芳, 钱敏慧, 戴赛, 刘新元. 计及运行风险和需求响应的两阶段鲁棒机组组合模型[J]. 中国电机工程学报, 2021, 41(3): 961-972. DOI: 10.13334/j.0258-8013.pcsee.200089
引用本文: 张智, 陈艳波, 刘芳, 钱敏慧, 戴赛, 刘新元. 计及运行风险和需求响应的两阶段鲁棒机组组合模型[J]. 中国电机工程学报, 2021, 41(3): 961-972. DOI: 10.13334/j.0258-8013.pcsee.200089
ZHANG Zhi, CHEN Yanbo, LIU Fang, QIAN Minhui, DAI Sai, LIU Xinyuan. Two-stage Robust Unit Commitment Model Considering Operation Risk and Demand Response[J]. Proceedings of the CSEE, 2021, 41(3): 961-972. DOI: 10.13334/j.0258-8013.pcsee.200089
Citation: ZHANG Zhi, CHEN Yanbo, LIU Fang, QIAN Minhui, DAI Sai, LIU Xinyuan. Two-stage Robust Unit Commitment Model Considering Operation Risk and Demand Response[J]. Proceedings of the CSEE, 2021, 41(3): 961-972. DOI: 10.13334/j.0258-8013.pcsee.200089

计及运行风险和需求响应的两阶段鲁棒机组组合模型

Two-stage Robust Unit Commitment Model Considering Operation Risk and Demand Response

  • 摘要: 高比例风电并网给电力系统的调度运行带来了挑战。为应对风电的不确定性,该文提出一种计及运行风险和需求响应的两阶段鲁棒机组组合(unit commitment,UC)模型,此模型具有以下特点:1)基于历史风电预测–实测数据分析了风电预测误差的分布特征,进而建立一种基于0-1规划的运行风险模型;2)将建立的运行风险模型与鲁棒UC模型结合,通过求解鲁棒UC模型动态地调整风电不确定集合的边界,实现运行成本和运行风险的协同优化;3)考虑分时电价对负荷需求的影响,并分析需求响应(demand response,DR)的不确定性对调度结果的影响。提出的模型采用Benders-C & CG方法进行求解。仿真结果表明,所提模型可动态地调整风电不确定集合边界,有效降低了运行成本和运行风险的总和。

     

    Abstract: The high proportion of wind power grid-connected brings challenges to power system dispatch and operation. To deal with the uncertainty of wind power, a two-stage robust unit commitment (UC) model considering operational risk and demand response was proposed in this paper. The model has the following characteristics: 1) Based on historical wind power prediction and measurement data, the distribution characteristics of wind power prediction errors were analyzed, and an operation risk model based on 0-1 programming was established; 2) Integrating the established operational risk model into the robust UC model, by solving the robust UC model and dynamically adjusting the boundary of the wind power admissibility area, the cooperative optimization of operational cost and operational risk was realized; 3) The influence of TOU price on load demand was considered, and the influence of demand response uncertainty on the dispatching result was analyzed. The proposed model was solved by Benders-C & CG method. The simulation results show that the proposed model can dynamically adjust the boundary of wind power uncertainty sets, and effectively reduce the total cost of operation cost and operation risk.

     

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